CFP last date
20 January 2025
Reseach Article

Storage Requirement Forecasting Analysis Model for Storage Area Networks

by P.Mahalingam, N.Jayaprakash, S.Karthikeyan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 19 - Number 6
Year of Publication: 2011
Authors: P.Mahalingam, N.Jayaprakash, S.Karthikeyan
10.5120/2367-3114

P.Mahalingam, N.Jayaprakash, S.Karthikeyan . Storage Requirement Forecasting Analysis Model for Storage Area Networks. International Journal of Computer Applications. 19, 6 ( April 2011), 13-17. DOI=10.5120/2367-3114

@article{ 10.5120/2367-3114,
author = { P.Mahalingam, N.Jayaprakash, S.Karthikeyan },
title = { Storage Requirement Forecasting Analysis Model for Storage Area Networks },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 19 },
number = { 6 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume19/number6/2367-3114/ },
doi = { 10.5120/2367-3114 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:16.571981+05:30
%A P.Mahalingam
%A N.Jayaprakash
%A S.Karthikeyan
%T Storage Requirement Forecasting Analysis Model for Storage Area Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 19
%N 6
%P 13-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Information management is an important area to concentrate for the business continuity of an organization. Organization should have a plan to store, retrieve and maintain its valuable information to meet the business demands. Storage Area Network (SAN) is a high performance network available to meet the enterprise storage solution. Since, SAN uses Fibre Channel (FC) as a transporting medium, it is considered to be fast, reliable and an optimum solution to handle the explosive growth of digital contents due to internet, application and use of modern gadgets. Various storage models are available for enterprise storage and choosing the relevant storage as per the business requirement needs careful analysis of the present and future storage consumption inside the organization. The SAN implementation in an organization involves many individual component analyses including storage requirement/capacity planning to handle the business information’s effectively and for the future. This research paper discusses a part of SAN implementation process, information generation, handling and information growth so that the SAN can be designed to meet the requirements. The aim of this paper is to analyze capacity of SAN as per the data generation and forecasting the data growth. The results were obtained for next five years in an organization using linear forecasting model to implement SAN as the enterprise storage solution.

References
  1. Kevin Craine. The Growth of Digital Information, April, 2001. Available: http://www.tdan.com/view-articles/4917
  2. Morries RJT & Truskowski BJ. The evolution of Storage Systems, IBM Systems Journal, Volume 42, Issue 2, Proquest Science Journal, 2003. pp.205-217
  3. Jamie Gruener, Research note: Compliance and digital-content growth drive content-storage market, The Yankee Group , May 20, 2003
  4. Odysseas I. Pentakalos, Daniel A. Menascé, Milton Halem, Yelena Yesha, Analytical Performance Modeling of Hierarchical Mass Storage Systems, IEEE Transactions on Computers, vol. 46, no. 10, pp. 1103-1118, October, 1997.
  5. G. A. Gibson, D. F. Nagle, K. Amiri, J. Butler, F. W. Chang, H. Gobioff, C. Hardin, E. Riedel, D. Rochberg, and J. Zelenka, "A cost-effective, high-bandwidth storage architecture," in ASPLOS-VIII: Proc. of 18th inter. conference on Architectural support for programming languages and operating systems, vol. 32, no. 5. New York, NY, USA: ACM Press, December 1998, pp. 92-103
  6. Gank and Rochester. Pirates of the digital millennium. FT Printice Hall, 2005, pg 175.
  7. Jhon F Gantz. The Diverse and Exploding Digital Universe – An IDC White Paper, Sponsored by IDC, March 2008.
  8. Aziz, M.H.Ong Con Nie, Jesse Chan Mei Yam & Lee Chang Wei. TCO reduction. Communications, 2003. APCC 2003. The 9th Asia-Pacific Conference. Volume: 3, On page(s): 1147- 1151 Vol.3. ISBN: 0-7803-8114-9, 2003.
  9. D. R. Avresky, V. Shurbanov, R. Horst, W. Watson, L. Young and D. Jewett. Performance Modeling of ServerNet™ SAN Topologies. ISSN. 0920-8542, Springer Netherlands, The Journal of Supercomputing, Computer Science, pp.19-37, December, 2004
  10. Storage Area Networks Design Reference Guide, Hewlett-Packard, pp.26. Sep 2003. Available: http://www.ost-india.com/services/san/understanding%20sans.pdf
  11. Jiwu Shu, Bigang Li, Weimin Zheng, "Design and Implementation of an SAN System Based on the Fiber Channel Protocol," IEEE Transactions on Computers, pp. 439-448, April, 2005
  12. Ng, J. M. and Susilo, R. N. Controlled shared backup strategy based on channel availability. Int. J. Comput. Appl. Technol. 24, 1 (Jun.2005), 25-32. DOI= http://dx.doi.org/10.1504/IJCAT.2005.007202
  13. Erik Riedel, Mahesh Kallahalla, and Ram Swaminathan. A Framework for Evaluating Storage System Security. Proc. of the 1st Conference on File and Storage Technologies (FAST’02), Monterey, CA, January, 2002.
  14. P.Mahalingam, N.Jayaprakash & S.Karthikeyan. Enhanced Data Security Framework for Storage Area Networks. Proc. Of the 2nd International Conference on Environmental and Computer Science (ICECS 2009, IEEE Explore), Dubai, UAE, pp105-110, 2009.
  15. Free Encyclopedia, Wikipedia. Available at http://en.wikipedia.org/wiki/Computer_data_storage
  16. Forecasting and Time Series Analysis using NCSS, NCSS, USA. http://www.ncss.com/4cast.html
  17. JE Beasley. Introduction to Forecasting, OR-Notes, http://people.brunel.ac.uk/~mastjjb/jeb/or/forecast.html
  18. Paul Ross. Design Considerations in Enterprise Storage Networks.
  19. Industry Trend or Event. Computer Technology Review, Nov, 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Information Management Information Growth Storage Area Networks SAN Design Storage Network Capacity Planning Linear Forecasting